How to use the salem.transform_geopandas function in salem

gdfc = gpd.GeoDataFrame()
    for i, ci in enumerate(catchment_indices):
        # Catchment polygon
        mask[:] = 0
        mask[tuple(ci.T)] = 1
        _, poly_no = _mask_to_polygon(mask, gdir=gdir)
        gdfc.loc[i, 'geometry'] = poly_no

    gdfi = utils.polygon_intersections(gdfc)

    # We project them onto the mercator proj before writing. This is a bit
    # inefficient (they'll be projected back later), but it's more sustainable
    gdfc.crs = gdir.grid
    gdfi.crs = gdir.grid
    salem.transform_geopandas(gdfc, gdir.grid.proj, inplace=True)
    salem.transform_geopandas(gdfi, gdir.grid.proj, inplace=True)
    if hasattr(gdfc.crs, 'srs'):
        # salem uses pyproj
        gdfc.crs = gdfc.crs.srs
        gdfi.crs = gdfi.crs.srs
    gdir.write_shapefile(gdfc, 'flowline_catchments')
    if len(gdfi) > 0:
        gdir.write_shapefile(gdfi, 'catchments_intersects')

grids_file = gdir.get_filepath('gridded_data')
    with ncDataset(grids_file) as nc:
        topo_smoothed = nc.variables['topo_smoothed'][:]
        glacier_mask = nc.variables['glacier_mask'][:]

    # Glacier exterior including nunataks
    erode = binary_erosion(glacier_mask)
    glacier_ext = glacier_mask ^ erode
    glacier_ext = np.where(glacier_mask == 1, glacier_ext, 0)

    # Intersects between glaciers
    gdfi = gpd.GeoDataFrame(columns=['geometry'])
    if gdir.has_file('intersects'):
        # read and transform to grid
        gdf = gdir.read_shapefile('intersects')
        salem.transform_geopandas(gdf, gdir.grid, inplace=True)
        gdfi = pd.concat([gdfi, gdf[['geometry']]])

    # Ice divide mask
    # Probably not the fastest way to do this, but it works
    dist = np.array([])
    jj, ii = np.where(glacier_ext)
    for j, i in zip(jj, ii):
        dist = np.append(dist, np.min(gdfi.distance(shpg.Point(i, j))))

    with warnings.catch_warnings():
        warnings.filterwarnings("ignore", category=RuntimeWarning)
        pok = np.where(dist <= 1)
    glacier_ext_intersect = glacier_ext * 0
    glacier_ext_intersect[jj[pok], ii[pok]] = 1

    # Distance from border mask - Scipy does the job

# I remove the boundary pixs because they are likely to be higher
    fpath = gdir.get_filepath('gridded_data', div_id=div_id)
    with netCDF4.Dataset(fpath) as nc:
        topo = nc.variables['topo'][:]
        mask_ext = nc.variables['glacier_ext'][:]
        mask_glacier = nc.variables['glacier_mask'][:]
    topo[np.where(mask_glacier == 0)] = np.NaN
    topo[np.where(mask_ext == 1)] = np.NaN

    # Intersects between catchments/glaciers
    gdfi = gpd.GeoDataFrame(columns=['geometry'])
    if gdir.has_file('catchments_intersects', div_id=div_id):
        # read and transform to grid
        gdf = gpd.read_file(gdir.get_filepath('catchments_intersects',
                                              div_id=div_id))
        salem.transform_geopandas(gdf, gdir.grid, inplace=True)
        gdfi = pd.concat([gdfi, gdf[['geometry']]])
    if gdir.has_file('divides_intersects', div_id=0):
        # read and transform to grid
        gdf = gpd.read_file(gdir.get_filepath('divides_intersects'))
        salem.transform_geopandas(gdf, gdir.grid, inplace=True)
        gdfi = pd.concat([gdfi, gdf[['geometry']]])
    if gdir.has_file('intersects', div_id=0):
        # read and transform to grid
        gdf = gpd.read_file(gdir.get_filepath('intersects', div_id=0))
        salem.transform_geopandas(gdf, gdir.grid, inplace=True)
        gdfi = pd.concat([gdfi, gdf[['geometry']]])

    # apply a buffer to be sure we get the intersects right. Be generous
    gdfi = gdfi.buffer(1.5)

    # Filter parameters

gdfc = gpd.GeoDataFrame()
    for i, ci in enumerate(catchment_indices):
        # Catchment polygon
        mask[:] = 0
        mask[tuple(ci.T)] = 1
        _, poly_no = _mask_to_polygon(mask, x=xmesh, y=ymesh, gdir=gdir)
        gdfc.loc[i, 'geometry'] = poly_no

    gdfi = utils.polygon_intersections(gdfc)

    # We project them onto the mercator proj before writing. This is a bit
    # inefficient (they'll be projected back later), but it's more sustainable
    gdfc.crs = gdir.grid
    gdfi.crs = gdir.grid
    salem.transform_geopandas(gdfc, gdir.grid.proj, inplace=True)
    salem.transform_geopandas(gdfi, gdir.grid.proj, inplace=True)
    if hasattr(gdfc.crs, 'srs'):
        # salem uses pyproj
        gdfc.crs = gdfc.crs.srs
        gdfi.crs = gdfi.crs.srs
    gdfc.to_file(gdir.get_filepath('flowline_catchments', div_id=div_id))
    if len(gdfi) > 0:
        gdfi.to_file(gdir.get_filepath('catchments_intersects',
                                       div_id=div_id))

gdfc = gpd.GeoDataFrame()
    for i, ci in enumerate(catchment_indices):
        # Catchment polygon
        mask[:] = 0
        mask[tuple(ci.T)] = 1
        _, poly_no = _mask_to_polygon(mask, gdir=gdir)
        gdfc.loc[i, 'geometry'] = poly_no

    gdfi = utils.polygon_intersections(gdfc)

    # We project them onto the mercator proj before writing. This is a bit
    # inefficient (they'll be projected back later), but it's more sustainable
    gdfc.crs = gdir.grid
    gdfi.crs = gdir.grid
    salem.transform_geopandas(gdfc, gdir.grid.proj, inplace=True)
    salem.transform_geopandas(gdfi, gdir.grid.proj, inplace=True)
    if hasattr(gdfc.crs, 'srs'):
        # salem uses pyproj
        gdfc.crs = gdfc.crs.srs
        gdfi.crs = gdfi.crs.srs
    gdir.write_shapefile(gdfc, 'flowline_catchments')
    if len(gdfi) > 0:
        gdir.write_shapefile(gdfi, 'catchments_intersects')

if not cfg.PARAMS['use_rgi_area']:
        # Update Area
        area = geometry.area * 1e-6
        entity['Area'] = area
        towrite['Area'] = area

    # Write shapefile
    gdir.write_shapefile(towrite, 'outlines')

    # Also transform the intersects if necessary
    gdf = cfg.PARAMS['intersects_gdf']
    if len(gdf) > 0:
        gdf = gdf.loc[((gdf.RGIId_1 == gdir.rgi_id) |
                       (gdf.RGIId_2 == gdir.rgi_id))]
        if len(gdf) > 0:
            gdf = salem.transform_geopandas(gdf, to_crs=proj_out)
            if hasattr(gdf.crs, 'srs'):
                # salem uses pyproj
                gdf.crs = gdf.crs.srs
            gdir.write_shapefile(gdf, 'intersects')
    else:
        # Sanity check
        if cfg.PARAMS['use_intersects']:
            raise InvalidParamsError('You seem to have forgotten to set the '
                                     'intersects file for this run. OGGM '
                                     'works better with such a file. If you '
                                     'know what your are doing, set '
                                     "cfg.PARAMS['use_intersects'] = False to "
                                     "suppress this error.")

    # 6. choose a spatial resolution with respect to the glacier area
    dxmethod = cfg.PARAMS['grid_dx_method']

mask_ext = nc.variables['glacier_ext'][:]
        mask_glacier = nc.variables['glacier_mask'][:]
    topo[np.where(mask_glacier == 0)] = np.NaN
    topo[np.where(mask_ext == 1)] = np.NaN

    # Intersects between catchments/glaciers
    gdfi = gpd.GeoDataFrame(columns=['geometry'])
    if gdir.has_file('catchments_intersects'):
        # read and transform to grid
        gdf = gdir.read_shapefile('catchments_intersects')
        salem.transform_geopandas(gdf, gdir.grid, inplace=True)
        gdfi = pd.concat([gdfi, gdf[['geometry']]])
    if gdir.has_file('intersects'):
        # read and transform to grid
        gdf = gdir.read_shapefile('intersects')
        salem.transform_geopandas(gdf, gdir.grid, inplace=True)
        gdfi = pd.concat([gdfi, gdf[['geometry']]])

    # apply a buffer to be sure we get the intersects right. Be generous
    gdfi = gdfi.buffer(1.5)

    # Filter parameters
    # Number of pixels to arbitrarily remove at junctions
    jpix = int(cfg.PARAMS['flowline_junction_pix'])

    # Loop over the lines
    mask = np.zeros((gdir.grid.ny, gdir.grid.nx))
    for fl, ci in zip(flowlines, catchment_indices):

        n = len(fl.dis_on_line)

        widths = np.zeros(n)